Generating Biomedical Knowledge Graphs from Knowledge Bases, Registries, and Multiomic Data.

ABSTRACT: As large clinical and multiomics datasets and knowledge resources accumulate, they need to be transformed into computable and actionable information to support automated reasoning. These datasets range from laboratory experiment results to electronic health records (EHRs). Barriers to accessibility and sharing of such datasets include diversity of content, size and privacy. Effective transformation of data into information requires harmonization of stakeholder goals, implementation, enforcement of standards regarding quality and completeness, and availability of resources for maintenance and updates. Systems such as the Biomedical Data Translator leverage knowledge graphs (KGs), structured and machine learning readable knowledge representation, to encode knowledge extracted through inferen

SUBMITTER: Qin G 

PROVIDER: S-EPMC11601480 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature